Explainable AI for Cervical Cancer: Accuracy, Ethics, and Clinical Trust explores the application of Explainable Artificial Intelligence (XAI) in cervical cancer detection, diagnosis, and prognosis. The book examines how AI-driven models can improve diagnostic accuracy while ensuring transparency, interpretability, and trustworthiness in clinical decision-making. It highlights the ethical, legal, and social implications of AI adoption in healthcare, emphasizing fairness, accountability, patient privacy, and clinician confidence. Through real-world case studies, advanced machine learning techniques, and emerging XAI frameworks, the book provides researchers, healthcare professionals, and policymakers with valuable insights into building reliable, ethical, and clinically trusted AI systems for cervical cancer management.
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